{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4dc1bf63",
   "metadata": {},
   "source": [
    "# 09-Synthetic-Control\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a6d9bc21",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:09.979160Z",
     "start_time": "2023-05-17T10:25:08.207794Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "from toolz.curried import *\n",
    "\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import statsmodels.formula.api as smf\n",
    "\n",
    "import seaborn as sns\n",
    "from matplotlib import pyplot as plt\n",
    "import matplotlib\n",
    "\n",
    "from cycler import cycler\n",
    "\n",
    "color=['0.0', '0.4', '0.8']\n",
    "default_cycler = (cycler(color=color))\n",
    "linestyle=['-', '--', ':', '-.']\n",
    "marker=['o', 'v', 'd', 'p']\n",
    "\n",
    "plt.rc('axes', prop_cycle=default_cycler)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f92a9c6",
   "metadata": {},
   "source": [
    "## Online Marketing Dataset\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "48236235",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.002094Z",
     "start_time": "2023-05-17T10:25:09.980748Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>app_download</th>\n",
       "      <th>population</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>date</th>\n",
       "      <th>post</th>\n",
       "      <th>treated</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3066.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-01</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2701.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-02</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1927.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-03</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1451.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-04</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1248.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-05</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   app_download  population       city      state       date  post  treated\n",
       "0        3066.0    12396372  sao_paulo  sao_paulo 2022-03-01     0        1\n",
       "1        2701.0    12396372  sao_paulo  sao_paulo 2022-03-02     0        1\n",
       "2        1927.0    12396372  sao_paulo  sao_paulo 2022-03-03     0        1\n",
       "3        1451.0    12396372  sao_paulo  sao_paulo 2022-03-04     0        1\n",
       "4        1248.0    12396372  sao_paulo  sao_paulo 2022-03-05     0        1"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "df = (pd.read_csv(\"./data/online_mkt.csv\")\n",
    "      .astype({\"date\":\"datetime64[ns]\"}))\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7a6932e9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.008563Z",
     "start_time": "2023-05-17T10:25:10.003416Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sao_paulo', 'porto_alegre', 'joao_pessoa']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "treated = list(df.query(\"treated==1\")[\"city\"].unique())\n",
    "treated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "077d1683",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.018732Z",
     "start_time": "2023-05-17T10:25:10.010696Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>app_download</th>\n",
       "      <th>population</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>date</th>\n",
       "      <th>post</th>\n",
       "      <th>treated</th>\n",
       "      <th>app_download_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3066.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-01</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.024733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2701.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-02</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.021789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1927.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-03</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.015545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1451.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-04</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.011705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1248.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-05</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.010067</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   app_download  population       city      state       date  post  treated  \\\n",
       "0        3066.0    12396372  sao_paulo  sao_paulo 2022-03-01     0        1   \n",
       "1        2701.0    12396372  sao_paulo  sao_paulo 2022-03-02     0        1   \n",
       "2        1927.0    12396372  sao_paulo  sao_paulo 2022-03-03     0        1   \n",
       "3        1451.0    12396372  sao_paulo  sao_paulo 2022-03-04     0        1   \n",
       "4        1248.0    12396372  sao_paulo  sao_paulo 2022-03-05     0        1   \n",
       "\n",
       "   app_download_pct  \n",
       "0          0.024733  \n",
       "1          0.021789  \n",
       "2          0.015545  \n",
       "3          0.011705  \n",
       "4          0.010067  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_norm = df.assign(\n",
    "    app_download_pct = 100*df[\"app_download\"]/df[\"population\"]\n",
    ")\n",
    "\n",
    "df_norm.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "54ba5315",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.025242Z",
     "start_time": "2023-05-17T10:25:10.019977Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2022-05-01 00:00:00')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tr_period = df_norm.query(\"post==1\")[\"date\"].min()\n",
    "tr_period"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3503e51a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.344779Z",
     "start_time": "2023-05-17T10:25:10.027147Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'app_download_pct')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(123)\n",
    "\n",
    "df_sc = df_norm.pivot(\"date\", \"city\", \"app_download_pct\")\n",
    "\n",
    "ax = df_sc[treated].mean(axis=1).plot(figsize=(15,6), label=\"$E[Y|D=1]$\")\n",
    "ax.vlines(tr_period, 0, 0.07, ls=\"dashed\", label=\"$t=T_{pre}+1$\")\n",
    "ax.legend()\n",
    "df_sc.drop(columns=treated).sample(frac=0.2, axis=1).plot(color=\"0.5\", alpha=0.2, legend=False, ax=ax)\n",
    "plt.ylabel(\"app_download_pct\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68a5e76f",
   "metadata": {},
   "source": [
    "## Matrix Representation\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6e3fae6e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.349222Z",
     "start_time": "2023-05-17T10:25:10.345921Z"
    }
   },
   "outputs": [],
   "source": [
    "def reshape_sc_data(df: pd.DataFrame,\n",
    "                    geo_col: str, \n",
    "                    time_col: str,\n",
    "                    y_col: str,\n",
    "                    tr_geos: str,\n",
    "                    tr_start: str):\n",
    "    \n",
    "    df_pivot = df.pivot(time_col, geo_col, y_col)\n",
    "    \n",
    "    y_co = df_pivot.drop(columns=tr_geos)\n",
    "    y_tr = df_pivot[tr_geos]\n",
    "    \n",
    "    y_pre_co = y_co[df_pivot.index < tr_start]\n",
    "    y_pre_tr = y_tr[df_pivot.index < tr_start]\n",
    "    \n",
    "    y_post_co = y_co[df_pivot.index >= tr_start]\n",
    "    y_post_tr = y_tr[df_pivot.index >= tr_start]\n",
    "    \n",
    "    return y_pre_co, y_pre_tr, y_post_co, y_post_tr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fc32b357",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.360157Z",
     "start_time": "2023-05-17T10:25:10.350374Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>city</th>\n",
       "      <th>sao_paulo</th>\n",
       "      <th>porto_alegre</th>\n",
       "      <th>joao_pessoa</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-03-01</th>\n",
       "      <td>0.024733</td>\n",
       "      <td>0.004288</td>\n",
       "      <td>0.022039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-02</th>\n",
       "      <td>0.021789</td>\n",
       "      <td>0.008107</td>\n",
       "      <td>0.020344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-03</th>\n",
       "      <td>0.015545</td>\n",
       "      <td>0.004891</td>\n",
       "      <td>0.012352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-04</th>\n",
       "      <td>0.011705</td>\n",
       "      <td>0.002948</td>\n",
       "      <td>0.018285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-05</th>\n",
       "      <td>0.010067</td>\n",
       "      <td>0.006767</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "city        sao_paulo  porto_alegre  joao_pessoa\n",
       "date                                            \n",
       "2022-03-01   0.024733      0.004288     0.022039\n",
       "2022-03-02   0.021789      0.008107     0.020344\n",
       "2022-03-03   0.015545      0.004891     0.012352\n",
       "2022-03-04   0.011705      0.002948     0.018285\n",
       "2022-03-05   0.010067      0.006767     0.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pre_co, y_pre_tr, y_post_co, y_post_tr = reshape_sc_data(\n",
    "    df_norm,\n",
    "    geo_col=\"city\",\n",
    "    time_col=\"date\",\n",
    "    y_col=\"app_download_pct\",\n",
    "    tr_geos=treated,\n",
    "    tr_start=str(tr_period)\n",
    ")\n",
    "\n",
    "y_pre_tr.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c52d481b",
   "metadata": {},
   "source": [
    "## Synthetic Control as Horizontal Regression\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f30ba6f8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.547010Z",
     "start_time": "2023-05-17T10:25:10.361564Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.65 , -0.058, -0.239,  0.971,  0.03 , -0.204,  0.007,  0.095,\n",
       "        0.102,  0.106,  0.074,  0.079,  0.032, -0.5  , -0.041, -0.154,\n",
       "       -0.014,  0.132,  0.115,  0.094,  0.151, -0.058, -0.353,  0.049,\n",
       "       -0.476, -0.11 ,  0.158, -0.002,  0.036, -0.129, -0.066,  0.024,\n",
       "       -0.047,  0.089, -0.057,  0.429,  0.23 , -0.086,  0.098,  0.351,\n",
       "       -0.128,  0.128, -0.205,  0.088,  0.147,  0.555,  0.229])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "model = LinearRegression(fit_intercept=False)\n",
    "model.fit(y_pre_co, y_pre_tr.mean(axis=1))\n",
    "\n",
    "# extract the weights\n",
    "weights_lr = model.coef_\n",
    "weights_lr.round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6be01d36",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.551856Z",
     "start_time": "2023-05-17T10:25:10.550040Z"
    }
   },
   "outputs": [],
   "source": [
    "# same as y0_tr_hat = model.predict(y_post_co)\n",
    "y0_tr_hat = y_post_co.dot(weights_lr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f0971ad9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.723571Z",
     "start_time": "2023-05-17T10:25:10.553366Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8e28115cd0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "\n",
    "y_co = pd.concat([y_pre_co, y_post_co])\n",
    "y_tr = pd.concat([y_pre_tr, y_post_tr])\n",
    "\n",
    "\n",
    "plt.plot(y_co.index, model.predict(y_co), label=\"Synthetic Control\", ls=\"-.\")\n",
    "plt.plot(y_tr.mean(axis=1), label=\"Treated Avg.\")\n",
    "plt.vlines(pd.to_datetime(\"2022-05-01\"), 0, 0.04, ls=\"dashed\", label=\"$t=T_{pre}+1$\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.ylabel(\"app_download_pct\")\n",
    "plt.legend(fontsize=14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0113ddda",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.727348Z",
     "start_time": "2023-05-17T10:25:10.724924Z"
    }
   },
   "outputs": [],
   "source": [
    "att = y_post_tr.mean(axis=1) - y0_tr_hat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2050500f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.845733Z",
     "start_time": "2023-05-17T10:25:10.728485Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8e7a93f590>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "plt.plot(y_tr.mean(axis=1) - model.predict(y_co), label=\"ATT\", ls=\"-.\")\n",
    "plt.vlines(pd.to_datetime(\"2022-05-01\"), att.min(), att.max(), ls=\"dashed\", label=\"$t=T_{pre}+1$\")\n",
    "plt.hlines(0, y_tr.index.min(), y_tr.index.max())\n",
    "plt.ylabel(\"ATT\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c42074c",
   "metadata": {},
   "source": [
    "## Canonical Synthetic Control\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "696b76e1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.977662Z",
     "start_time": "2023-05-17T10:25:10.847322Z"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.base import BaseEstimator, RegressorMixin\n",
    "from sklearn.utils.validation import (check_X_y, check_array,\n",
    "                                      check_is_fitted)\n",
    "import cvxpy as cp\n",
    "\n",
    "class SyntheticControl(BaseEstimator, RegressorMixin):\n",
    "\n",
    "    def __init__(self,):\n",
    "        pass\n",
    "\n",
    "    def fit(self, y_pre_co, y_pre_tr):\n",
    "\n",
    "        y_pre_co, y_pre_tr = check_X_y(y_pre_co, y_pre_tr)\n",
    "    \n",
    "        w = cp.Variable(y_pre_co.shape[1])\n",
    "        \n",
    "        objective = cp.Minimize(cp.sum_squares(y_pre_co@w - y_pre_tr))\n",
    "        constraints = [cp.sum(w) == 1, w >= 0]\n",
    "        \n",
    "        problem = cp.Problem(objective, constraints)\n",
    "        \n",
    "        self.loss_ = problem.solve(verbose=False)\n",
    "        self.w_ = w.value\n",
    "        \n",
    "        self.is_fitted_ = True\n",
    "        return self\n",
    "        \n",
    "        \n",
    "    def predict(self, y_co):\n",
    "\n",
    "        check_is_fitted(self)\n",
    "        y_co = check_array(y_co)\n",
    "        \n",
    "        return y_co @ self.w_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e317d02f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:10.993252Z",
     "start_time": "2023-05-17T10:25:10.978785Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.   , -0.   , -0.   , -0.   , -0.   , -0.   ,  0.076,  0.037,\n",
       "        0.083,  0.01 , -0.   , -0.   , -0.   , -0.   , -0.   , -0.   ,\n",
       "        0.061,  0.123,  0.008,  0.074, -0.   ,  0.   , -0.   , -0.   ,\n",
       "       -0.   , -0.   , -0.   , -0.   , -0.   ,  0.   , -0.   ,  0.092,\n",
       "       -0.   , -0.   ,  0.   ,  0.046,  0.089,  0.   ,  0.067,  0.061,\n",
       "        0.   , -0.   , -0.   ,  0.088,  0.   ,  0.086, -0.   ])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = SyntheticControl()\n",
    "model.fit(y_pre_co, y_pre_tr.mean(axis=1))\n",
    "\n",
    "# extrac the weights\n",
    "model.w_.round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b3a5d525",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:11.213147Z",
     "start_time": "2023-05-17T10:25:10.994770Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(15,8), sharex=True)\n",
    "\n",
    "ax1.plot(y_co.index, model.predict(y_co), label=\"Synthetic Control\")\n",
    "ax1.plot(y_tr.mean(axis=1), label=\"Treated\", ls=\"-.\")\n",
    "ax1.vlines(pd.to_datetime(\"2022-05-01\"), 0, 0.04, ls=\"dashed\", label=\"$T_0$\")\n",
    "ax1.legend()\n",
    "ax1.set_ylabel(\"ATT\")\n",
    "\n",
    "ax2.plot(y_co.index, y_tr.mean(axis=1) - model.predict(y_co), label=\"Effect\", ls=\"-.\")\n",
    "ax2.hlines(0, y_co.index.min(), y_co.index.max())\n",
    "ax2.vlines(pd.to_datetime(\"2022-05-01\"), -0.01, 0.015, label=\"$T_0$\")\n",
    "ax2.legend()\n",
    "ax2.set_ylabel(\"app_download_pct\")\n",
    "\n",
    "plt.xticks(rotation=45);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "714ea01b",
   "metadata": {},
   "source": [
    "## Synthetic Control with Covariants\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "dd4ce6f6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:11.230768Z",
     "start_time": "2023-05-17T10:25:11.214295Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>app_download</th>\n",
       "      <th>population</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>date</th>\n",
       "      <th>post</th>\n",
       "      <th>treated</th>\n",
       "      <th>app_download_pct</th>\n",
       "      <th>comp_download_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3066.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-01</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.024733</td>\n",
       "      <td>0.026280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2701.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-02</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.021789</td>\n",
       "      <td>0.023925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1927.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-03</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.015545</td>\n",
       "      <td>0.018930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1451.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-04</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.011705</td>\n",
       "      <td>0.015858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1248.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>2022-03-05</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.010067</td>\n",
       "      <td>0.014548</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   app_download  population       city      state       date  post  treated  \\\n",
       "0        3066.0    12396372  sao_paulo  sao_paulo 2022-03-01     0        1   \n",
       "1        2701.0    12396372  sao_paulo  sao_paulo 2022-03-02     0        1   \n",
       "2        1927.0    12396372  sao_paulo  sao_paulo 2022-03-03     0        1   \n",
       "3        1451.0    12396372  sao_paulo  sao_paulo 2022-03-04     0        1   \n",
       "4        1248.0    12396372  sao_paulo  sao_paulo 2022-03-05     0        1   \n",
       "\n",
       "   app_download_pct  comp_download_pct  \n",
       "0          0.024733           0.026280  \n",
       "1          0.021789           0.023925  \n",
       "2          0.015545           0.018930  \n",
       "3          0.011705           0.015858  \n",
       "4          0.010067           0.014548  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_norm_cov = (pd.read_csv(\"./data/online_mkt_cov.csv\")\n",
    "               .astype({\"date\":\"datetime64[ns]\"}))\n",
    "\n",
    "df_norm_cov.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "849c9a54",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:11.241710Z",
     "start_time": "2023-05-17T10:25:11.232244Z"
    }
   },
   "outputs": [],
   "source": [
    "from toolz import partial\n",
    "\n",
    "reshaper = partial(reshape_sc_data,\n",
    "                   df=df_norm_cov,\n",
    "                   geo_col=\"city\",\n",
    "                   time_col=\"date\",\n",
    "                   tr_geos=treated,\n",
    "                   tr_start=str(tr_period))\n",
    "\n",
    "y_pre_co, y_pre_tr, y_post_co, y_post_tr = reshaper(\n",
    "    y_col=\"app_download_pct\"\n",
    ")\n",
    "\n",
    "x_pre_co, _, x_post_co, _ = reshaper(y_col=\"comp_download_pct\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8e86032e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:11.257578Z",
     "start_time": "2023-05-17T10:25:11.242829Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.   , -0.   ,  0.   , -0.   , -0.   , -0.   ,  0.084,  0.039,\n",
       "        0.085,  0.003, -0.   , -0.   , -0.   , -0.   , -0.   ,  0.   ,\n",
       "        0.062,  0.121, -0.   ,  0.072, -0.   ,  0.   , -0.   ,  0.   ,\n",
       "       -0.   , -0.   ,  0.   , -0.   , -0.   ,  0.   , -0.   ,  0.095,\n",
       "        0.   , -0.   ,  0.   ,  0.022,  0.116, -0.   ,  0.068,  0.046,\n",
       "       -0.   , -0.   , -0.   ,  0.088,  0.   ,  0.098, -0.   ])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def find_w_given_vs(vs, x_co_list, y_tr_pre):\n",
    "    X_times_v = sum([x*v for x, v in zip(x_co_list, vs)])\n",
    "    \n",
    "    model = SyntheticControl()\n",
    "    model.fit(X_times_v, y_tr_pre)\n",
    "    \n",
    "    return {\"loss\": model.loss_, \"w\": model.w_} \n",
    "\n",
    "\n",
    "find_w_given_vs([1, 0],\n",
    "                [y_pre_co, x_pre_co],\n",
    "                y_pre_tr.mean(axis=1)).get(\"w\").round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5da887cb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:11.877851Z",
     "start_time": "2023-05-17T10:25:11.259071Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.88034589, 0.00269853])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.optimize import minimize\n",
    "\n",
    "def v_loss(vs):\n",
    "    return find_w_given_vs(vs,\n",
    "                           [y_pre_co, x_pre_co],\n",
    "                           y_pre_tr.mean(axis=1)).get(\"loss\")\n",
    "\n",
    "\n",
    "v_solution = minimize(v_loss, [0, 0], method='L-BFGS-B')\n",
    "v_solution.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6163957e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:11.889948Z",
     "start_time": "2023-05-17T10:25:11.878865Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.   , -0.   ,  0.   , -0.   , -0.   , -0.   ,  0.078,  0.001,\n",
       "        0.033,  0.   , -0.   ,  0.034, -0.   , -0.   , -0.   ,  0.   ,\n",
       "        0.016,  0.047,  0.03 ,  0.01 , -0.   , -0.   ,  0.   ,  0.055,\n",
       "       -0.   ,  0.   , -0.   ,  0.   ,  0.   ,  0.   , -0.   ,  0.046,\n",
       "        0.078,  0.007,  0.   ,  0.   ,  0.138,  0.   ,  0.022,  0.008,\n",
       "       -0.   ,  0.201,  0.   ,  0.035,  0.   ,  0.161, -0.   ])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_cov = find_w_given_vs(v_solution.x,\n",
    "                        [y_pre_co, x_pre_co],\n",
    "                        y_pre_tr.mean(axis=1)).get(\"w\").round(3)\n",
    "\n",
    "w_cov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "06511fcf",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:11.895084Z",
     "start_time": "2023-05-17T10:25:11.891231Z"
    }
   },
   "outputs": [],
   "source": [
    "y0_hat = sum([x*v for x, v \n",
    "              in zip([y_post_co, x_post_co], v_solution.x)]).dot(w_cov)\n",
    "\n",
    "att = y_post_tr.mean(axis=1) - y0_hat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7d9d4ed8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:12.005495Z",
     "start_time": "2023-05-17T10:25:11.896525Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "plt.plot(y_co.index, y_tr.mean(axis=1) - model.predict(y_co), label=\"w/o covariates\", ls=\"-.\")\n",
    "plt.plot(att.index, att, label=\"w/ covariates\")\n",
    "\n",
    "\n",
    "plt.hlines(0, y_co.index.min(), y_co.index.max())\n",
    "plt.vlines(pd.to_datetime(\"2022-05-01\"), -0.01, 0.015)\n",
    "plt.legend()\n",
    "plt.ylabel(\"ATT\")\n",
    "plt.xticks(rotation=45);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4043cde7",
   "metadata": {},
   "source": [
    "## Debiasing Synthetic Control\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "24166ad2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:14.725014Z",
     "start_time": "2023-05-17T10:25:12.007242Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8e609bac50>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.tsa.arima_process import ArmaProcess\n",
    "\n",
    "def sim_sc_data(N=16, T0=15, T1=28):\n",
    "    Y_co = np.random.normal(\n",
    "        np.array([np.concatenate([np.ones(3), np.zeros(N-3)])*2 for _ in range(T0+T1)])\n",
    "    )\n",
    "    \n",
    "    w = np.concatenate([np.ones(3), np.zeros(N-3)])*1/3\n",
    "    Y_tr = Y_co.dot(w) + ArmaProcess(0.8).generate_sample(T0+T1)\n",
    "    \n",
    "    model = SyntheticControl().fit(\n",
    "        y_pre_co=Y_co[:T0],\n",
    "        y_pre_tr=Y_tr[:T0].flatten()\n",
    "    )\n",
    "        \n",
    "    return (Y_tr[T0:].flatten() - model.predict(Y_co[T0:])).mean()\n",
    "\n",
    "\n",
    "np.random.seed(123)\n",
    "\n",
    "atts = [sim_sc_data() for _ in range(500)]\n",
    "\n",
    "plt.figure(figsize=(10,4))\n",
    "plt.hist(atts, alpha=0.2, density=True, bins=20)\n",
    "plt.vlines(np.mean(atts), 0, 1.5, label=\"Simulation Avg.\")\n",
    "plt.vlines(0, 0, 1.5, label=\"Correct ATT\", ls=\"dashed\")\n",
    "plt.title(\"500 SC Simulations\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6edf34c2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:14.730990Z",
     "start_time": "2023-05-17T10:25:14.726827Z"
    }
   },
   "outputs": [],
   "source": [
    "def debiased_sc_atts(y_pre_co, y_pre_tr, y_post_co, y_post_tr, K=3):\n",
    "        \n",
    "    block_size = int(min(np.floor(len(y_pre_tr)/K), len(y_post_tr)))\n",
    "    blocks = np.split(y_pre_tr.index[-K*block_size:], K)\n",
    "    \n",
    "    def fold_effect(hold_out):\n",
    "        model = SyntheticControl()\n",
    "        model.fit(\n",
    "            y_pre_co.drop(hold_out),\n",
    "            y_pre_tr.drop(hold_out)\n",
    "        )\n",
    "        \n",
    "        bias_hat = np.mean(y_pre_tr.loc[hold_out]\n",
    "                           - model.predict(y_pre_co.loc[hold_out]))\n",
    "        \n",
    "        y0_hat = model.predict(y_post_co)\n",
    "        return (y_post_tr - y0_hat) - bias_hat\n",
    "    \n",
    "    \n",
    "    return pd.DataFrame([fold_effect(block) for block in blocks]).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "949d5858",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:14.770112Z",
     "start_time": "2023-05-17T10:25:14.732323Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-05-01</th>\n",
       "      <td>0.003314</td>\n",
       "      <td>0.002475</td>\n",
       "      <td>0.003322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-02</th>\n",
       "      <td>0.003544</td>\n",
       "      <td>0.002844</td>\n",
       "      <td>0.003355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-03</th>\n",
       "      <td>0.004644</td>\n",
       "      <td>0.003698</td>\n",
       "      <td>0.004743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-04</th>\n",
       "      <td>0.004706</td>\n",
       "      <td>0.002866</td>\n",
       "      <td>0.003675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-05</th>\n",
       "      <td>0.000134</td>\n",
       "      <td>-0.000541</td>\n",
       "      <td>0.000315</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   0         1         2\n",
       "date                                    \n",
       "2022-05-01  0.003314  0.002475  0.003322\n",
       "2022-05-02  0.003544  0.002844  0.003355\n",
       "2022-05-03  0.004644  0.003698  0.004743\n",
       "2022-05-04  0.004706  0.002866  0.003675\n",
       "2022-05-05  0.000134 -0.000541  0.000315"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deb_atts = debiased_sc_atts(y_pre_co,\n",
    "                            y_pre_tr.mean(axis=1),\n",
    "                            y_post_co,\n",
    "                            y_post_tr.mean(axis=1),\n",
    "                            K=3)\n",
    "\n",
    "deb_atts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a98ec0eb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:14.886831Z",
     "start_time": "2023-05-17T10:25:14.771587Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "model_biased = SyntheticControl()\n",
    "model_biased.fit(y_pre_co, y_pre_tr.mean(axis=1))\n",
    "\n",
    "att_biased = y_post_tr.mean(axis=1) - model_biased.predict(y_post_co)\n",
    "\n",
    "plt.figure(figsize=(10,4))\n",
    "plt.plot(att, label=\"ATT Debiased\", ls=\"-.\")\n",
    "plt.plot(att_biased, label=\"ATT Biased\")\n",
    "plt.legend()\n",
    "plt.hlines(0, att.index.min(), att.index.max())\n",
    "plt.ylabel(\"ATT\")\n",
    "plt.xticks(rotation=45);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "aa50717a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.465867Z",
     "start_time": "2023-05-17T10:25:14.894424Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8e58f9b650>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sim_deb_sc_data(N=16, T0=15, T1=28):\n",
    "    Y_co = np.random.normal(\n",
    "        np.array([np.concatenate([np.ones(3), np.zeros(N-3)])*2 for _ in range(T0+T1)])\n",
    "    )\n",
    "    \n",
    "    w = np.concatenate([np.ones(3), np.zeros(N-3)])*1/3\n",
    "    Y_tr = Y_co.dot(w) + ArmaProcess(0.8).generate_sample(T0+T1)\n",
    "    \n",
    "    df_co = pd.DataFrame(Y_co)\n",
    "    df_tr = pd.DataFrame(Y_tr)\n",
    "    \n",
    "    atts = debiased_sc_atts(df_co.iloc[:T0],\n",
    "                            df_tr.iloc[:T0].mean(axis=1),\n",
    "                            df_co.iloc[T0:],\n",
    "                            df_tr.iloc[T0:].mean(axis=1), K=2)\n",
    "    \n",
    "        \n",
    "    return atts.mean(axis=0).mean()\n",
    "\n",
    "\n",
    "np.random.seed(123)\n",
    "atts = [sim_deb_sc_data() for _ in range(500)]\n",
    "\n",
    "plt.figure(figsize=(10,4))\n",
    "plt.hist(atts, alpha=0.2, density=True, bins=20)\n",
    "plt.vlines(np.mean(atts), 0, 1.0, label=\"Sample Avg.\")\n",
    "plt.vlines(0, 0, 1, label=\"Correct ATT\", ls=\"dashed\")\n",
    "plt.title(\"500 SC (Debiased) Simulations\")\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "800a531b",
   "metadata": {},
   "source": [
    "## Inference\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "08edfa11",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.472291Z",
     "start_time": "2023-05-17T10:25:22.467461Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-05-01</th>\n",
       "      <td>0.003314</td>\n",
       "      <td>0.002475</td>\n",
       "      <td>0.003322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-02</th>\n",
       "      <td>0.003544</td>\n",
       "      <td>0.002844</td>\n",
       "      <td>0.003355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-03</th>\n",
       "      <td>0.004644</td>\n",
       "      <td>0.003698</td>\n",
       "      <td>0.004743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-04</th>\n",
       "      <td>0.004706</td>\n",
       "      <td>0.002866</td>\n",
       "      <td>0.003675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-05</th>\n",
       "      <td>0.000134</td>\n",
       "      <td>-0.000541</td>\n",
       "      <td>0.000315</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   0         1         2\n",
       "date                                    \n",
       "2022-05-01  0.003314  0.002475  0.003322\n",
       "2022-05-02  0.003544  0.002844  0.003355\n",
       "2022-05-03  0.004644  0.003698  0.004743\n",
       "2022-05-04  0.004706  0.002866  0.003675\n",
       "2022-05-05  0.000134 -0.000541  0.000315"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deb_atts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c7257ec4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.477021Z",
     "start_time": "2023-05-17T10:25:22.473794Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "atts_k: [0.00414872 0.00260513 0.00322101]\n",
      "ATT: 0.003324950193632595\n"
     ]
    }
   ],
   "source": [
    "atts_k = deb_atts.mean(axis=0).values\n",
    "att = np.mean(atts_k)\n",
    "\n",
    "print(\"atts_k:\", atts_k)\n",
    "print(\"ATT:\", att)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ce30c148",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.482049Z",
     "start_time": "2023-05-17T10:25:22.478281Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SE: 0.0006318346108228888\n"
     ]
    }
   ],
   "source": [
    "K = len(atts_k)\n",
    "T0 = len(y_pre_co)\n",
    "T1 = len(y_post_co)\n",
    "block_size = min(np.floor(T0/K), T1)\n",
    "\n",
    "se_hat=np.sqrt(1+((K*block_size)/T1))*np.std(atts_k, ddof=1)/np.sqrt(K)\n",
    "\n",
    "print(\"SE:\", se_hat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "53fc37e2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.487547Z",
     "start_time": "2023-05-17T10:25:22.483584Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.0014800022408602205, 0.005169898146404969]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import t\n",
    "alpha = 0.1\n",
    "\n",
    "[att - t.ppf(1-alpha/2, K-1)*se_hat,\n",
    " att + t.ppf(1-alpha/2, K-1)*se_hat]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d052807",
   "metadata": {},
   "source": [
    "## Synthetic Difference-in-Differences\n",
    "\n",
    "### DID Refresher\n",
    "\n",
    "\n",
    "### Synthetic Controls Revisited\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "9d7b10e6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.503287Z",
     "start_time": "2023-05-17T10:25:22.489069Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.003327040979396121"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sc_model = SyntheticControl()\n",
    "sc_model.fit(y_pre_co, y_pre_tr.mean(axis=1))\n",
    "\n",
    "(y_post_tr.mean(axis=1) - sc_model.predict(y_post_co)).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "3b0ffab9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.510495Z",
     "start_time": "2023-05-17T10:25:22.504502Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "      <th>unit_weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ananindeua</td>\n",
       "      <td>-0.000008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>aparecida_de_goiania</td>\n",
       "      <td>-0.000001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>aracaju</td>\n",
       "      <td>-0.000008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>belem</td>\n",
       "      <td>-0.000012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>belford_roxo</td>\n",
       "      <td>-0.000006</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   city  unit_weight\n",
       "0            ananindeua    -0.000008\n",
       "1  aparecida_de_goiania    -0.000001\n",
       "2               aracaju    -0.000008\n",
       "3                 belem    -0.000012\n",
       "4          belford_roxo    -0.000006"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unit_w = pd.DataFrame(zip(y_pre_co.columns, sc_model.w_),\n",
    "                         columns=[\"city\", \"unit_weight\"])\n",
    "\n",
    "unit_w.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ce16e895",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.513929Z",
     "start_time": "2023-05-17T10:25:22.511952Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "pd.set_option('display.max_columns', 7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0968d9b9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.528310Z",
     "start_time": "2023-05-17T10:25:22.515662Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>app_download</th>\n",
       "      <th>population</th>\n",
       "      <th>city</th>\n",
       "      <th>...</th>\n",
       "      <th>app_download_pct</th>\n",
       "      <th>tr_post</th>\n",
       "      <th>unit_weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3066.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>...</td>\n",
       "      <td>0.024733</td>\n",
       "      <td>0</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2701.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>...</td>\n",
       "      <td>0.021789</td>\n",
       "      <td>0</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1927.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015545</td>\n",
       "      <td>0</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1451.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>...</td>\n",
       "      <td>0.011705</td>\n",
       "      <td>0</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1248.0</td>\n",
       "      <td>12396372</td>\n",
       "      <td>sao_paulo</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010067</td>\n",
       "      <td>0</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   app_download  population       city  ... app_download_pct tr_post  \\\n",
       "0        3066.0    12396372  sao_paulo  ...         0.024733       0   \n",
       "1        2701.0    12396372  sao_paulo  ...         0.021789       0   \n",
       "2        1927.0    12396372  sao_paulo  ...         0.015545       0   \n",
       "3        1451.0    12396372  sao_paulo  ...         0.011705       0   \n",
       "4        1248.0    12396372  sao_paulo  ...         0.010067       0   \n",
       "\n",
       "   unit_weight  \n",
       "0         0.06  \n",
       "1         0.06  \n",
       "2         0.06  \n",
       "3         0.06  \n",
       "4         0.06  \n",
       "\n",
       "[5 rows x 10 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_with_w = (df_norm\n",
    "             .assign(tr_post = lambda d: d[\"post\"]*d[\"treated\"])\n",
    "             .merge(unit_w, on=[\"city\"], how=\"left\")\n",
    "             .fillna({\"unit_weight\": df_norm[\"treated\"].mean()}))\n",
    "             \n",
    "df_with_w.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d747f813",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.616625Z",
     "start_time": "2023-05-17T10:25:22.529640Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0033293800074678703"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mod = smf.wls(\n",
    "    \"app_download_pct ~ tr_post + C(date)\",\n",
    "    data=df_with_w.query(\"unit_weight>=1e-10\"),\n",
    "    weights=df_with_w.query(\"unit_weight>=1e-10\")[\"unit_weight\"]\n",
    ")\n",
    "\n",
    "mod.fit().params[\"tr_post\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a29a7d85",
   "metadata": {},
   "source": [
    "### Estimating Time Weights\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "7d7e9511",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.623285Z",
     "start_time": "2023-05-17T10:25:22.618413Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "from sklearn.base import BaseEstimator, RegressorMixin\n",
    "from sklearn.utils.validation import check_X_y, check_array, check_is_fitted\n",
    "import cvxpy as cp\n",
    "\n",
    "class SyntheticControl(BaseEstimator, RegressorMixin):\n",
    "\n",
    "    def __init__(self, fit_intercept=False):\n",
    "        self.fit_intercept = fit_intercept\n",
    "\n",
    "    def fit(self, y_pre_co, y_pre_tr):\n",
    "\n",
    "        y_pre_co, y_pre_tr = check_X_y(y_pre_co, y_pre_tr)\n",
    "        \n",
    "        # add intercept\n",
    "        intercept = np.ones((y_pre_co.shape[0], 1))*self.fit_intercept\n",
    "        X = np.concatenate([intercept, y_pre_co], axis=1)\n",
    "        w = cp.Variable(X.shape[1])\n",
    "        \n",
    "        objective = cp.Minimize(cp.sum_squares(X@w - y_pre_tr))\n",
    "        constraints = [cp.sum(w[1:]) == 1, w[1:] >= 0]\n",
    "        \n",
    "        problem = cp.Problem(objective, constraints)\n",
    "        \n",
    "        self.loss_ = problem.solve(verbose=False)\n",
    "        self.w_ = w.value[1:] # remove intercept\n",
    "        \n",
    "        self.is_fitted_ = True\n",
    "        return self\n",
    "        \n",
    "        \n",
    "    def predict(self, y_co):\n",
    "\n",
    "        check_is_fitted(self)\n",
    "        y_co = check_array(y_co)\n",
    "        \n",
    "        return y_co @ self.w_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "b0d6f619",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.640940Z",
     "start_time": "2023-05-17T10:25:22.624929Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>time_weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2022-04-26</td>\n",
       "      <td>-0.000011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>0.071965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2022-04-28</td>\n",
       "      <td>-0.000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2022-04-29</td>\n",
       "      <td>0.078350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2022-04-30</td>\n",
       "      <td>0.000002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date  time_weight\n",
       "56 2022-04-26    -0.000011\n",
       "57 2022-04-27     0.071965\n",
       "58 2022-04-28    -0.000002\n",
       "59 2022-04-29     0.078350\n",
       "60 2022-04-30     0.000002"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_sc = SyntheticControl(fit_intercept=True)\n",
    "\n",
    "time_sc.fit(\n",
    "    y_pre_co.T,\n",
    "    y_post_co.mean(axis=0)\n",
    ")\n",
    "\n",
    "time_w = pd.DataFrame(zip(y_pre_co.index, time_sc.w_),\n",
    "                         columns=[\"date\", \"time_weight\"])\n",
    "\n",
    "time_w.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "e0bda8b6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.779115Z",
     "start_time": "2023-05-17T10:25:22.642620Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure(figsize=(10,4))\n",
    "plt.bar(time_w[\"date\"], time_w[\"time_weight\"])\n",
    "plt.ylabel(\"Time Weights\")\n",
    "plt.xticks(rotation=45);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e05c1a8a",
   "metadata": {},
   "source": [
    "### Synthetic Control and DID\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "67ca2010",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.787947Z",
     "start_time": "2023-05-17T10:25:22.780992Z"
    }
   },
   "outputs": [],
   "source": [
    "scdid_df = (\n",
    "    df_with_w\n",
    "    .merge(time_w, on=[\"date\"], how=\"left\")\n",
    "    .fillna({\"time_weight\":df_norm[\"post\"].mean()})\n",
    "    .assign(weight = lambda d: (d[\"time_weight\"]*d[\"unit_weight\"]))\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "17d30d87",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:22.801647Z",
     "start_time": "2023-05-17T10:25:22.789299Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.004086196404101931"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "did_model = smf.wls(\n",
    "    \"app_download_pct ~ treated*post\",\n",
    "    data=scdid_df.query(\"weight>1e-10\"),\n",
    "    weights=scdid_df.query(\"weight>1e-10\")[\"weight\"]).fit()\n",
    "\n",
    "did_model.params[\"treated:post\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "6c05684d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-17T10:25:23.112689Z",
     "start_time": "2023-05-17T10:25:22.803269Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "avg_pre_period = time_w.iloc[int((time_w[\"time_weight\"] * np.arange(0, len(time_w), 1)).sum().round())][\"date\"]\n",
    "avg_post_period = pd.Timestamp(\"2022-06-01\")\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(15,8), sharex=True, gridspec_kw={'height_ratios': [3, 1]})\n",
    "\n",
    "ax1.plot(y_co.index, y_tr.mean(axis=1), label=\"Treated\")\n",
    "ax1.plot(y_co.index, sc_model.predict(y_co), label=\"Synthetic Control\", ls=\"-.\")\n",
    "ax1.vlines(tr_period, y_tr.mean(axis=1).min(), y_tr.mean(axis=1).max(), color=\"black\", ls=\"dotted\")\n",
    "\n",
    "pre_sc = did_model.params[\"Intercept\"]\n",
    "post_sc = pre_sc + did_model.params[\"post\"]\n",
    "pre_treat = pre_sc + did_model.params[\"treated\"]\n",
    "post_treat = post_sc + did_model.params[\"treated\"] + did_model.params[\"treated:post\"]\n",
    "\n",
    "sc_did_y0 = pre_treat + (post_sc - pre_sc)\n",
    "\n",
    "ax1.plot([avg_pre_period, avg_post_period], [pre_treat, post_treat], color=\"C2\", ls=\"dashed\")\n",
    "ax1.plot([avg_pre_period, avg_post_period], [pre_treat, sc_did_y0], color=\"C2\")\n",
    "ax1.legend()\n",
    "ax1.set_title(\"Synthetic Diff-in-Diff\")\n",
    "ax1.set_ylabel(\"app_download_pct\")\n",
    "\n",
    "ax2.bar(time_w[\"date\"], time_w[\"time_weight\"])\n",
    "ax2.vlines(tr_period, 0, 0.15, color=\"black\", ls=\"dotted\")\n",
    "ax2.set_ylabel(\"Time Weights\")\n",
    "ax2.set_xlabel(\"Dates\")\n",
    "plt.xticks(rotation=30);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c08ddbda",
   "metadata": {},
   "source": [
    "## Key Ideas\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "803670fb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Tags",
  "kernelspec": {
   "display_name": "Python [conda env:root] *",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
